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计算机工程 ›› 2008, Vol. 34 ›› Issue (5): 210-212. doi: 10.3969/j.issn.1000-3428.2008.05.074

• 人工智能及识别技术 • 上一篇    下一篇

基于Contourlet变换和Wiener滤波的图像降噪

刘盛鹏,方 勇   

  1. (上海大学通信与信息工程学院,上海 200072)
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2008-03-05 发布日期:2008-03-05

Image Denosing Based on Contourlet Transform and Wiener Filter

LIU Sheng-peng, FANG Yong   

  1. (School of Communication and Information Engineering, Shanghai University, Shanghai 200072)
  • Received:1900-01-01 Revised:1900-01-01 Online:2008-03-05 Published:2008-03-05

摘要: 提出一种新的基于Contourlet变换和Wiener滤波的图像降噪方法。该方法充分利用Contourlet变换域系数服从广义高斯分布的特点,在Contourlet域采用Bayes收缩阈值法进行预降噪,采用Wiener滤波法对预降噪图像中的残留噪声进行进一步处理,以提高图像的恢复精度。仿真结果表明,该方法较传统的Contourlet域降噪方法具有更好的降噪效果,进一步提高了PSNR值,降低了MSE值,获得了更好的图像恢复质量。

关键词: 图像处理, Contourlet变换, Wiener滤波, 预降噪图像

Abstract: A new image denosing method based on Contourlet transform and Wiener filtering is proposed. By using the statistical information, the Contourlet domain coefficients of the original image are estimated by Bayes shrink threshold algorithm. For further denoising, the final denoising image will be estimated through Wiener filtering. Experimental results show that the denoising effect of this method is better than that of other methods based on Contourlet transform.

Key words: image processing, Contourlet transform, Wiener filtering, pre-denoised image

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